Reduced complexity coefficient transmission for adaptive loop filtering (ALF) in video coding

ABSTRACT

A method for adaptive loop filtering is provided that includes determining a coefficient value for each coefficient position of an adaptive loop filter, applying the adaptive loop filter to at least a portion of a reconstructed picture using the coefficient values, and entropy encoding coefficient values into a compressed bit stream using predetermined short binary codes, wherein the short binary code used depends on the coefficient position of the coefficient value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/858,920, filed Apr. 8, 2013 which claims benefit of U.S. ProvisionalPatent Application Ser. No. 61/622,237, filed Apr. 10, 2012, U.S.Provisional Patent Application Ser. No. 61/623,323, filed Apr. 12, 2012,and U.S. Provisional Patent Application Ser. No. 61/661,997, filed Jun.20, 2012, which are incorporated herein by reference in their entirety.

BACKGROUND OF THE INVENTION Field of the Invention

Embodiments of the present invention generally relate to encoding anddecoding of adaptive loop filter coefficients in video coding.

Description of the Related Art

Video compression, i.e., video coding, is an essential enabler fordigital video products as it enables the storage and transmission ofdigital video. In general, video compression techniques applyprediction, transformation, quantization, and entropy coding tosequential blocks of pixels in a video sequence to compress, i.e.,encode, the video sequence. Video decompression techniques generallyperform the inverse of these operations in reverse order to decompress,i.e., decode, a compressed video sequence.

The Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T WP3/16and ISO/IEC JTC 1/SC 29/WG 11 is currently developing thenext-generation video coding standard referred to as High EfficiencyVideo Coding (HEVC). HEVC is expected to provide around 50% improvementin coding efficiency over the current standard, H.264/AVC, as well aslarger resolutions and higher frame rates. To address theserequirements, HEVC utilizes larger block sizes then H.264/AVC. In HEVC,the largest coding unit (LCU) can be up to 64×64 in size, while inH.264/AVC, the macroblock size is fixed at 16×16.

Adaptive loop filtering (ALF) is a new coding tool proposed for HEVC. Ingeneral, ALF is an adaptive Wiener filtering technique applied after thedeblocking filter to improve the reference picture used forencoding/decoding of subsequent pictures. The original ALF concept isexplained in more detail in Y. Chiu and L. Xu, “Adaptive (Wiener) Filterfor Video Compression,” ITU-T SG16 Contribution, C437, Geneva, CH, April2008. As originally proposed, ALF used square filters and was carriedout on entire deblocked pictures. Subsequently, block-based adaptiveloop filtering was proposed in which ALF could be enabled and disabledon a block, i.e., coding unit, basis. In block-based ALF, the encodersignals to the decoder the map of blocks of a deblocked picture on whichALF is to be applied. Block-based ALF is described in more detail in T.Chujoh, et al., “Block-based Adaptive Loop Filter,” ITU-T SG16 Q.6Document, VCEG-A118, Berlin, DE, July 2008.

A further refinement to block-based ALF, quadtree adaptive loopfiltering, was subsequently proposed in which the map of blocks wassignaled using a quadtree. Quadtree ALF is described in more detail inT. Chujoh, et al., “Quadtree-based Adaptive Loop Filter,” ITU-T SG16Contribution, C181, January 2009. The use of diamond shaped rather thansquare shaped ALF filters was then proposed to reduce computationalcomplexity. Diamond shaped ALF filters for luma components are describedin more detail in M. Karczewicz, et al., “A Hybrid Video Coder Based onExtended Macroblock Sizes, Improved Interpolation, and Flexible MotionRepresentation,” IEEE Trans. on Circuits and Systems for VideoTechnology, pp. 1698-1708, Vol. 20, No. 12, December 2010.

SUMMARY

Embodiments of the present invention relate to methods and apparatus foradaptive loop filtering in video coding. In one aspect, a method foradaptive loop filtering is provided that includes determining acoefficient value for each coefficient position of an adaptive loopfilter, applying the adaptive loop filter to at least a portion of areconstructed picture using the coefficient values, and entropy encodingcoefficient values into a compressed bit stream using predeterminedshort binary codes, wherein the short binary code used depends on thecoefficient position of the coefficient value.

In one aspect, a method for adaptive loop filtering is provided thatincludes entropy decoding coefficient values from a compressed video bitstream using predetermined short binary codes, wherein the short binarycode used depends on the coefficient position of the coefficient value,and applying the adaptive loop filter to at least a portion of areconstructed picture using the coefficient values.

In one aspect, an apparatus configured to perform adaptive loopfiltering is provided that includes means for determining a coefficientvalue for each coefficient position of an adaptive loop filter, meansfor applying the adaptive loop filter to at least a portion of areconstructed picture using the coefficient values, and means forentropy encoding coefficient values into a compressed bit stream usingpredetermined short binary codes, wherein the short binary code useddepends on the coefficient position of the coefficient value.

BRIEF DESCRIPTION OF THE DRAWINGS

Particular embodiments will now be described, by way of example only,and with reference to the accompanying drawings:

FIG. 1 is an example of an adaptive loop filter (ALF);

FIG. 2 is a flow diagram of a prior art method for encoding thecoefficient values of the filter of FIG. 1;

FIG. 3 is a block diagram of a digital system;

FIG. 4 is a block diagram of a video encoder;

FIG. 5 is a block diagram of a video decoder;

FIGS. 6-17 and 20-23 are flow diagrams of methods;

FIGS. 18 and 19 are examples of the distributions of ALF coefficientvalues; and

FIG. 24 is a block diagram of an illustrative digital system.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

Specific embodiments of the invention will now be described in detailwith reference to the accompanying figures. Like elements in the variousfigures are denoted by like reference numerals for consistency.

As used herein, the term “picture” may refer to a frame or a field of aframe. A frame is a complete image captured during a known timeinterval. For convenience of description, embodiments of the inventionare described herein in reference to HEVC. One of ordinary skill in theart will understand that embodiments of the invention are not limited toHEVC.

In HEVC, a largest coding unit (LCU) is the base unit used forblock-based coding. A picture is divided into non-overlapping LCUs. Thatis, an LCU plays a similar role in coding as the macroblock ofH.264/AVC, but it may be larger, e.g., 32×32, 64×64, etc. An LCU may bepartitioned into coding units (CU). A CU is a block of pixels within anLCU and the CUs within an LCU may be of different sizes. Thepartitioning is a recursive quadtree partitioning. The quadtree is splitaccording to various criteria until a leaf is reached, which is referredto as the coding node or coding unit. The maximum hierarchical depth ofthe quadtree is determined by the size of the smallest CU (SCU)permitted. The coding node is the root node of two trees, a predictiontree and a transform tree. A prediction tree specifies the position andsize of prediction units (PU) for a coding unit. A transform treespecifies the position and size of transform units (TU) for a codingunit. A transform unit may not be larger than a coding unit and the sizeof a transform unit may be, for example, 4×4, 8×8, 16×16, and 32×32. Thesizes of the transforms units and prediction units for a CU aredetermined by the video encoder during prediction based on minimizationof rate/distortion costs.

Some aspects of this disclosure have been presented to the JCT-VC in thefollowing documents: JCTVC-I0381, entitled “ALF Filter CoefficientsDistribution and Modifications to Coding”, Apr. 7, 2012-May 7, 2012, andJCTVC-I0346, entitled “Simplification of ALF Filter Coefficients Coding,Apr. 7, 2012-May 7, 2012. These documents are incorporated by referenceherein in their entirety.

As previously discussed, adaptive loop filtering (ALF) is a new codingtool proposed in HEVC. As currently proposed, ALF uses a 10-tapsymmetric two-dimensional (2D) filter as shown in FIG. 1. The filtercoefficients C0, C1, . . . , C9 are predicted and transmitted asfollows. Up to sixteen ALF filter sets may be transmitted for the lumacomponent of an LCU in addition to one ALF filter set each for the twochroma components of the LCU. Two types of prediction have been proposedto reduce the bit rate for ALF coefficient transmission—intra filterprediction and inter filter prediction. Further, two types of intrafilter prediction are proposed—prediction of the filter coefficient C8and prediction of the filter coefficient C9. Intra filter prediction ofC8 and inter filter prediction were observed to provide no bit ratesavings and are expected to be removed. The description below describesthe prior art assuming that intra filter prediction of C8 and interfilter prediction are not used.

The ALF filter coefficients are encoded in the compressed bit streamusing Golomb-code using fixed k-parameters for each coefficient. Table 1shows the k parameter values for each ALF filter coefficient, the valuerange of each coefficient, and the worst case codeword length for eachcoefficient. FIG. 2 is a flow chart illustrating the entropy coding ofthe ALF coefficients using Golomb code and the values of k specified inTable 2. There are two issues with using this coding scheme: 1) theentropy coding is filter position dependent and changes from coefficientto coefficient; and 2) the worst case codeword length for eachcoefficient is very large, e.g., as much as 131 bits for k=1. Variablelength decoding of such large code words is difficult for 32- and 64-bitprocessors.

TABLE 1 Golomb (k) Filter Coefficient Max length Syntax elementcoefficient value range k (in bits) alf_filt_coeff[0] C0 −256 to 255 268 alf_filt_coeff[1] C1 −256 to 255 3 37 alf_filt_coeff[2] C2 −256 to255 3 37 alf_filt_coeff[3] C3 −256 to 255 4 22 alf_filt_coeff[4] C4 −256to 255 3 37 alf_filt_coeff[5] C5 −256 to 255 1 131 alf_filt_coeff[6] C6−256 to 255 2 68 alf_filt_coeff[7] C7 −256 to 255 3 37 alf_filt_coeff[8]C8 −256 to 255 4 22 alf_filt_coeff[9] C9 0 to 511 1 258

Embodiments of the invention provide for simplification of the coding ofthe ALF filter coefficients. In some embodiments, the ALF filter isconstrained to be unit gain filter such that the value of C9 can bederived from the values of C0 . . . C8, thus eliminating the need totransmit C9 in the encoded bit stream. In some embodiments, coefficientposition independent entropy coding techniques are used. In someembodiments, coefficient position dependent entropy coding techniqueswith smaller worst case codeword lengths are used. In some embodiments,coefficient position dependent entropy coding techniques usingexp-Golomb codes in which the value of k may vary by coefficientposition are used. In some embodiments, coefficient position dependententropy coding techniques using a combination of exp-Golomb codes andfixed length codes are used. In some embodiments, a bias is subtractedfrom ALF filter coefficients before the coefficients are entropy coded.

FIG. 3 shows a block diagram of a digital system that includes a sourcedigital system 300 that transmits encoded video sequences to adestination digital system 302 via a communication channel 316. Thesource digital system 300 includes a video capture component 304, avideo encoder component 306, and a transmitter component 308. The videocapture component 304 is configured to provide a video sequence to beencoded by the video encoder component 306. The video capture component304 may be, for example, a video camera, a video archive, or a videofeed from a video content provider. In some embodiments, the videocapture component 304 may generate computer graphics as the videosequence, or a combination of live video, archived video, and/orcomputer-generated video.

The video encoder component 306 receives a video sequence from the videocapture component 304 and encodes it for transmission by the transmittercomponent 308. The video encoder component 306 receives the videosequence from the video capture component 304 as a sequence of pictures,divides the pictures into largest coding units (LCUs), and encodes thevideo data in the LCUs. The video encoder component 306 may beconfigured to apply adaptive loop filter coefficient encoding techniquesduring the encoding process as described herein. An embodiment of thevideo encoder component 306 is described in more detail herein inreference to FIG. 4.

The transmitter component 308 transmits the encoded video data to thedestination digital system 302 via the communication channel 316. Thecommunication channel 316 may be any communication medium, orcombination of communication media suitable for transmission of theencoded video sequence, such as, for example, wired or wirelesscommunication media, a local area network, or a wide area network.

The destination digital system 302 includes a receiver component 310, avideo decoder component 312 and a display component 314. The receivercomponent 310 receives the encoded video data from the source digitalsystem 300 via the communication channel 316 and provides the encodedvideo data to the video decoder component 312 for decoding. The videodecoder component 312 reverses the encoding process performed by thevideo encoder component 306 to reconstruct the LCUs of the videosequence. The video decoder component 312 may be configured to applyadaptive loop filter coefficient decoding techniques during the decodingprocess as described herein. An embodiment of the video decodercomponent 312 is described in more detail below in reference to FIG. 5.

The reconstructed video sequence is displayed on the display component314. The display component 314 may be any suitable display device suchas, for example, a plasma display, a liquid crystal display (LCD), alight emitting diode (LED) display, etc.

In some embodiments, the source digital system 300 may also include areceiver component and a video decoder component and/or the destinationdigital system 302 may include a transmitter component and a videoencoder component for transmission of video sequences both directionsfor video steaming, video broadcasting, and video telephony. Further,the video encoder component 306 and the video decoder component 312 mayperform encoding and decoding in accordance with one or more videocompression standards. The video encoder component 306 and the videodecoder component 312 may be implemented in any suitable combination ofsoftware, firmware, and hardware, such as, for example, one or moredigital signal processors (DSPs), microprocessors, discrete logic,application specific integrated circuits (ASICs), field-programmablegate arrays (FPGAs), etc.

FIG. 4 is a block diagram of the LCU processing portion of an examplevideo encoder. A coding control component (not shown) sequences thevarious operations of the LCU processing, i.e., the coding controlcomponent runs the main control loop for video encoding. The codingcontrol component receives a digital video sequence and performs anyprocessing on the input video sequence that is to be done at the picturelevel, such as determining the coding type (I, P, or B) of a picturebased on the high level coding structure, e.g., IPPP, IBBP,hierarchical-B, and dividing a picture into LCUs for further processing.

In addition, for pipelined architectures in which multiple LCUs may beprocessed concurrently in different components of the LCU processing,the coding control component controls the processing of the LCUs byvarious components of the LCU processing in a pipeline fashion. Forexample, in many embedded systems supporting video processing, there maybe one master processor and one or more slave processing modules, e.g.,hardware accelerators. The master processor operates as the codingcontrol component and runs the main control loop for video encoding, andthe slave processing modules are employed to off load certaincompute-intensive tasks of video encoding such as motion estimation,motion compensation, intra prediction mode estimation, transformationand quantization, entropy coding, and loop filtering. The slaveprocessing modules are controlled in a pipeline fashion by the masterprocessor such that the slave processing modules operate on differentLCUs of a picture at any given time. That is, the slave processingmodules are executed in parallel, each processing its respective LCUwhile data movement from one processor to another is serial.

The LCU processing receives LCUs 400 of the input video sequence fromthe coding control component and encodes the LCUs 400 under the controlof the coding control component to generate the compressed video stream.The LCUs 400 in each picture are processed in row order. The LCUs 400from the coding control component are provided as one input of a motionestimation component (ME) 420, as one input of an intra-predictionestimation component (IPE) 424, and to a positive input of a combiner402 (e.g., adder or subtractor or the like). Further, although notspecifically shown, the prediction mode of each picture as selected bythe coding control component is provided to a mode decision component428 and the entropy coding component 436.

The storage component 418 provides reference data to the motionestimation component 420 and to the motion compensation component 422.The reference data may include one or more previously encoded anddecoded pictures, i.e., reference pictures.

The motion estimation component 420 provides motion data information tothe motion compensation component 422 and the entropy coding component436. More specifically, the motion estimation component 420 performstests on CUs in an LCU based on multiple inter-prediction modes (e.g.,skip mode, merge mode, and normal or direct inter-prediction), PU sizes,and TU sizes using reference picture data from storage 418 to choose thebest CU partitioning, PU/TU partitioning, inter-prediction modes, motionvectors, etc. based on coding cost, e.g., a rate distortion coding cost.To perform the tests, the motion estimation component 420 may divide anLCU into CUs according to the maximum hierarchical depth of thequadtree, and divide each CU into PUs according to the unit sizes of theinter-prediction modes and into TUs according to the transform unitsizes, and calculate the coding costs for each PU size, prediction mode,and transform unit size for each CU. The motion estimation component 420provides the motion vector (MV) or vectors and the prediction mode foreach PU in the selected CU partitioning to the motion compensationcomponent (MC) 422.

The motion compensation component 422 receives the selectedinter-prediction mode and mode-related information from the motionestimation component 420 and generates the inter-predicted CUs. Theinter-predicted CUs are provided to the mode decision component 428along with the selected inter-prediction modes for the inter-predictedPUs and corresponding TU sizes for the selected CU/PU/TU partitioning.The coding costs of the inter-predicted CUs are also provided to themode decision component 428.

The intra-prediction estimation component 424 (IPE) performsintra-prediction estimation in which tests on CUs in an LCU based onmultiple intra-prediction modes, PU sizes, and TU sizes are performedusing reconstructed data from previously encoded neighboring CUs storedin a buffer (not shown) to choose the best CU partitioning, PU/TUpartitioning, and intra-prediction modes based on coding cost, e.g., arate distortion coding cost. To perform the tests, the intra-predictionestimation component 424 may divide an LCU into CUs according to themaximum hierarchical depth of the quadtree, and divide each CU into PUsaccording to the unit sizes of the intra-prediction modes and into TUsaccording to the transform unit sizes, and calculate the coding costsfor each PU size, prediction mode, and transform unit size for each PU.The intra-prediction estimation component 424 provides the selectedintra-prediction modes for the PUs, and the corresponding TU sizes forthe selected CU partitioning to the intra-prediction component (IP) 426.The coding costs of the intra-predicted CUs are also provided to theintra-prediction component 426.

The intra-prediction component 426 (IP) receives intra-predictioninformation, e.g., the selected mode or modes for the PU(s), the PUsize, etc., from the intra-prediction estimation component 424 andgenerates the intra-predicted CUs. The intra-predicted CUs are providedto the mode decision component 428 along with the selectedintra-prediction modes for the intra-predicted PUs and corresponding TUsizes for the selected CU/PU/TU partitioning. The coding costs of theintra-predicted CUs are also provided to the mode decision component428.

The mode decision component 428 selects between intra-prediction of a CUand inter-prediction of a CU based on the intra-prediction coding costof the CU from the intra-prediction component 426, the inter-predictioncoding cost of the CU from the motion compensation component 422, andthe picture prediction mode provided by the coding control component.Based on the decision as to whether a CU is to be intra- or inter-coded,the intra-predicted PUs or inter-predicted PUs are selected. Theselected CU/PU/TU partitioning with corresponding modes and other moderelated prediction data (if any) such as motion vector(s) and referencepicture index (indices), are provided to the entropy coding component436.

The output of the mode decision component 428, i.e., the predicted PUs,is provided to a negative input of the combiner 402 and to the combiner438. The associated transform unit size is also provided to thetransform component 404. The combiner 402 subtracts a predicted PU fromthe original PU. Each resulting residual PU is a set of pixel differencevalues that quantify differences between pixel values of the original PUand the predicted PU. The residual blocks of all the PUs of a CU form aresidual CU for further processing.

The transform component 404 performs block transforms on the residualCUs to convert the residual pixel values to transform coefficients andprovides the transform coefficients to a quantize component 406. Morespecifically, the transform component 404 receives the transform unitsizes for the residual CU and applies transforms of the specified sizesto the CU to generate transform coefficients. Further, the quantizecomponent 406 quantizes the transform coefficients based on quantizationparameters (QPs) and quantization matrices provided by the codingcontrol component and the transform sizes and provides the quantizedtransform coefficients to the entropy coding component 436 for coding inthe bit stream.

The entropy coding component 436 entropy encodes the relevant data,i.e., syntax elements, output by the various encoding components and thecoding control component using context-adaptive binary arithmetic coding(CABAC) to generate the compressed video bit stream. Among the syntaxelements that are encoded are picture parameter sets, flags indicatingthe CU/PU/TU partitioning of an LCU, the prediction modes for the CUs,and the quantized transform coefficients for the CUs. The entropy codingcomponent 436 also codes relevant data from the in-loop filters(described below) such as the adaptive loop filter (ALF) coefficientsfor each picture. Methods for encoding ALF coefficients that may be usedby the entropy coding component 436 are described below in reference toFIGS. 6, 8, 10, 12, 14, 16, and 20.

The LCU processing includes an embedded decoder. As any compliantdecoder is expected to reconstruct an image from a compressed bitstream, the embedded decoder provides the same utility to the videoencoder. Knowledge of the reconstructed input allows the video encoderto transmit the appropriate residual energy to compose subsequentpictures.

The quantized transform coefficients for each CU are provided to aninverse quantize component (IQ) 412, which outputs a reconstructedversion of the transform result from the transform component 404. Thedequantized transform coefficients are provided to the inverse transformcomponent (IDCT) 414, which outputs estimated residual informationrepresenting a reconstructed version of a residual CU. The inversetransform component 414 receives the transform unit size used togenerate the transform coefficients and applies inverse transform(s) ofthe specified size to the transform coefficients to reconstruct theresidual values. The reconstructed residual CU is provided to thecombiner 438.

The combiner 438 adds the original predicted CU to the residual CU togenerate a reconstructed CU, which becomes part of reconstructed picturedata. The reconstructed picture data is stored in a buffer (not shown)for use by the intra-prediction estimation component 424.

Various in-loop filters may be applied to the reconstructed picture datato improve the quality of the reference picture data used forencoding/decoding of subsequent pictures. The in-loop filters mayinclude a deblocking filter component 430, a sample adaptive offsetfilter (SAO) component 432, and an adaptive loop filter (ALF) component434. The in-loop filters 430, 432, 434 are applied to each reconstructedLCU in the picture and the final filtered reference picture data isprovided to the storage component 418.

The ALF component 434 selectively applies a symmetric 2D finite impulseresponse (FIR) filter of the shape shown in FIG. 1 to blocks of thereconstructed picture. In general, for a given block, the ALF component434 determines a set of filter coefficients, and applies the filter tothe block using the set of filter coefficients. The filter parametersare determined using a standard Weiner filtering technique in which theobjective is to determine parameters such that the mean squared errorbetween the original input pixels and the filtered reconstructed pixelsis minimized. As part of determining the filter coefficients, the ALFcomponent 434 may apply a coding cost versus error decrease analysis todecide whether or not a particular block is to be filtered. Thus, someblocks may be not be filtered. The sets of filter coefficients andinformation regarding whether to filter a particular block are providedto the entropy coding component 436 to be encoded in the bit stream.Information regarding which coefficients sets are to be used for whichblocks can be derived at both the encoder and the decoder based on blockstatistics (e.g., variance) or based on the picture region in which theblock resides.

FIG. 5 is a block diagram of an example video decoder. The video decoderoperates to reverse the encoding operations, i.e., entropy coding,quantization, transformation, and prediction, performed by the videoencoder of FIG. 4 to regenerate the pictures of the original videosequence. In view of the above description of a video encoder, one ofordinary skill in the art will understand the functionality ofcomponents of the video decoder without detailed explanation.

The entropy decoding component 500 receives an entropy encoded(compressed) video bit stream and reverses the entropy encoding usingCABAC decoding to recover the encoded syntax elements, e.g., CU, PU, andTU structures of LCUs, quantized transform coefficients for CUs, motionvectors, prediction modes, ALF coefficients, etc. The decoded syntaxelements are passed to the various components of the decoder as needed.For example, decoded prediction modes are provided to theintra-prediction component (IP) 514 or motion compensation component(MC) 510. If the decoded prediction mode is an inter-prediction mode,the entropy decoder 500 reconstructs the motion vector(s) as needed andprovides the motion vector(s) to the motion compensation component 510.In another example, decoded ALF coefficients are provided to the ALFcomponent 520. Methods for decoding ALF coefficients that may be used bythe entropy decoding component 500 are described below in reference toFIGS. 7, 9, 11, 13, 15, 17, and 21.

The inverse quantize component (IQ) 502 de-quantizes the quantizedtransform coefficients of the CUs. The inverse transform component 504transforms the frequency domain data from the inverse quantize component502 back to the residual CUs. That is, the inverse transform component504 applies an inverse unit transform, i.e., the inverse of the unittransform used for encoding, to the de-quantized residual coefficientsto produce reconstructed residual values of the CUs.

A residual CU supplies one input of the addition component 506. Theother input of the addition component 506 comes from the mode switch508. When an inter-prediction mode is signaled in the encoded videostream, the mode switch 508 selects predicted PUs from the motioncompensation component 510 and when an intra-prediction mode issignaled, the mode switch selects predicted PUs from theintra-prediction component 514.

The motion compensation component 510 receives reference data from thestorage component 512 and applies the motion compensation computed bythe encoder and transmitted in the encoded video bit stream to thereference data to generate a predicted PU. That is, the motioncompensation component 510 uses the motion vector(s) from the entropydecoder 500 and the reference data to generate a predicted PU.

The intra-prediction component 514 receives reconstructed samples frompreviously reconstructed PUs of a current picture from the storagecomponent 512 and performs the intra-prediction computed by the encoderas signaled by an intra-prediction mode transmitted in the encoded videobit stream using the reconstructed samples as needed to generate apredicted PU.

The addition component 506 generates a reconstructed CU by adding thepredicted PUs selected by the mode switch 508 and the residual CU. Theoutput of the addition component 506, i.e., the reconstructed CUs, isstored in the storage component 512 for use by the intra-predictioncomponent 514.

In-loop filters may be applied to reconstructed picture data to improvethe quality of the decoded pictures and the quality of the referencepicture data used for decoding of subsequent pictures. The appliedin-loop filters are the same as those of the encoder, i.e., a deblockingfilter 516, a sample adaptive offset filter (SAO) 518, and an adaptiveloop filter (ALF) 520. The in-loop filters may be applied on anLCU-by-LCU basis and the final filtered reference picture data isprovided to the storage component 512.

The ALF component 520 applies the same symmetric 2D FIR filter of thesame shape to blocks of the reconstructed picture using the sets ofcoefficients signaled in the compressed bit stream. More specifically,for each block in a reconstructed picture, the ALF component 520 appliesthe filter using the filter coefficients determined for that block bythe encoder.

Various methods for entropy encoding ALF filter coefficients togetherwith corresponding methods for entropy decoding are now described. Thesemethods assume the symmetric filter of FIG. 1. One of ordinary skill inart, having benefit of this disclosure, will understand embodiments forother filter shapes and/or embodiments in which ALF uses multiple filtershapes. In general, the symmetric filter shape may be a diamond, circle,star, cross, or any other general shape bounded by a (2V+1)×(2H+1)rectangle where V is the vertical dimension of the filter and H is thehorizontal dimension of the filter. In practice, the filter shape orshapes to be used are defined by the video coding standard, e.g., HEVC.

As previously mentioned, as currently defined in HEVC, ALF filtercoefficients are encoded in the bit stream using Golomb coding of orderk where the value of k is dependent of the coefficient position. As iswell known, Golomb coding uses the parameter k to divide an input valueinto two parts: the quotient of a division by k, and the remainder ofthe division by k. The quotient is encoded using unary coding and theremainder is encoded using binary encoding. More specifically, theoutput of G(k) coding as used in HEVC is a three part code word thatincludes a unary prefix of one bits, a binary suffix, and a separatorbetween the prefix and suffix that is a single zero bit. To encode anon-negative integer n using a Golomb code of order k, the quotient qand remainder r of n with respect to 2^(k) is calculated as shown in Eq.(1) and Eq. (2), respectively. Note that r corresponds to the kleast-significant bits of the binary representation of n, and qcorresponds to the other, most-significant, bits. The codeword for nconsists of a prefix of q one bits, the single zero bit separator, and asuffix of k bits containing the binary representation of r. Further, thelength of the codeword for n is q+1+k.q=n>>k  (1)r=n−q*2^(k)  (2)The use of Golomb coding with the values of k specified by HEVC canresult in very large worst case codeword lengths.

FIGS. 6, 8, 10, 12, and 14 are flow diagrams of methods for encoding thefilter coefficients with a smaller worst case codeword length, and FIGS.7, 9, 11, 13, and 15 are flow diagrams of corresponding methods fordecoding the filter coefficients. One of ordinary skill in the art,having benefit of the disclosure herein, will understand the decodingmethods without need for additional description. The methods useexponential Golomb (exp-Golomb) codes, or exp-Golomb codes incombination with truncated unary (TU) or fixed length codes (FLC).Similar to Golomb codes, exp-Golomb codes are indexed by a non-negativeinteger value k. Furthermore, the output of the particular EG(k) codingused is a three part code word that includes a unary prefix of one bits,a binary suffix, and a separator between the prefix and suffix that is asingle zero bit. More specifically, to encode a non-negative integer nusing an exp-Golomb code of order k, the number of one bits q in theprefix of the codeword may be calculated as shown in Eq. (3) and thevalue r of the suffix may be calculated as shown in Eq. (4). The lengthof the suffix is q+k. The codeword for n consists of a prefix q onebits, the single zero bit separator, and a suffix of q+k bits containingthe binary representation of r. The codeword may also be obtaineddirectly as the binary representation of the sum n+2^(k), zero-extendedby q bits. Further, the length of the codeword for n is 2q+k+1.q=log₂((n+2^(k))>>k)  (3)r=n+2^(k)−2^(q+k)  (4)Exp-Golomb coding of integers m with negative and non-negative valuescan be carried out by mapping the negative and non-negative values of minto positive values n. An example mapping is as follows:

-   -   mapping from m to n:        -   if(m<=0) n=−2*m        -   else n=2*m−1    -   mapping from n to m:        -   if (n & 0×1) m=(n+1)/2        -   else m=−n/2.

In truncated unary (TU) coding, if an integer value x to be coded isless than a truncated value S, the coded result is x continuous “1” bitsfollowed by a terminating “0” bit. Otherwise, the coded result is Scontinuous “1” bits. For example, let S=3. If x=2, the coded result is“110”. If x=3, the coded result is “111”. In fixed length coding (FLC)of order S, each code word has a fixed bit length of S.

FIG. 6 is a flow diagram of a method for encoding ALF filtercoefficients using coefficient position dependent short codes, i.e.,exp-Golomb codes of order k=0, . . . , 5, where the value of k dependson the position of a coefficient. FIG. 7 is a flow diagram of thecorresponding method for decoding ALF filter coefficients encoded usingthe method of FIG. 6. Table 2 shows the value of k for each coefficientposition and the maximum codeword length for the coefficient position.The particular values of k shown in FIGS. 6 and 7 and in Table 2 foreach coefficient position are examples. Other suitable values may beused. For example, values for k may be determined based on theprobability distribution of the values of coefficients C0 . . . C9 for arepresentative test set. Distributions with fatter tails may be assignedlarger values of k while distributions which are peaked around a value(typically 0) may be assigned smaller values of k. The probabilitydistribution of a coefficient position can be overlaid by thecorresponding probability distribution of the variable length code(obtained as 2^(Li) where Li is the length of codeword i) for differentvalues of k and the k with the best corresponding distribution selectedfor the coefficient position.

FIG. 8 is a flow diagram of a method for encoding ALF filtercoefficients using a single coefficient position dependent short code,e.g., an exp-Golomb code of order k=0 (EG(0)), for some coefficientpositions, and using a combination of coefficient position dependentshort codes, i.e., truncated unary (TU) code in combination withexp-Golomb code, for other coefficient positions, e.g., a combination ofa TU of order S=3 (TU(3)) and EG(0). FIG. 9 is a flow diagram of thecorresponding method for decoding ALF filter coefficients encoded usingthe method of FIG. 8. Table 3 shows the values of k and S (whereapplicable) for each coefficient position and the maximum codewordlength for the coefficient position. Table 4 is the code table forTU3+EG(0). The particular values of k and S shown in FIGS. 8 and 9 andin Table 3 for each coefficient position are examples. Other suitablevalues may be used. For example, the values of k and S may be determinedas described above in reference to FIGS. 6 and 7. The particular use ofEG(0) alone or TU(3) in combination with EG(0) for a coefficientposition are also examples. For this example, TU(3) in combination withEG(0) is used for coefficient positions with peaked distributions.

TABLE 2 Filter Coefficient Max length Syntax element coefficient valuerange k (in bits) alf_filt_coeff[0] C0 −256 to 255 1 17alf_filt_coeff[1] C1 −256 to 255 2 16 alf_filt_coeff[2] C2 −256 to 255 315 alf_filt_coeff[3] C3 −256 to 255 4 14 alf_filt_coeff[4] C4 −256 to255 3 15 alf_filt_coeff[5] C5 −256 to 255 1 17 alf_filt_coeff[6] C6 −256to 255 3 15 alf_filt_coeff[7] C7 −256 to 255 3 15 alf_filt_coeff[8] C8−256 to 255 5 13 alf_filt_coeff[9] C9 0 to 511 0 20

TABLE 3 Entropy Filter coding Coefficient Max length Syntax elementcoefficient technique value range (in bits) alf_filt_coeff[0] C0 TU3 +EG0 −256 to 255 20 alf_filt_coeff[1] C1 EG0 −256 to 255 17alf_filt_coeff[2] C2 EG0 −256 to 255 17 alf_filt_coeff[3] C3 EG0 −256 to255 17 alf_filt_coeff[4] C4 EG0 −256 to 255 17 alf_filt_coeff[5] C5TU3 + EG0 −256 to 255 20 alf_filt_coeff[6] C6 TU3 + EG0 −256 to 255 20alf_filt_coeff[7] C7 EG0 −256 to 255 17 alf_filt_coeff[8] C8 EG0 −256 to255 17 alf_filt_coeff[9] C9 TU3 + EG0 0 to 511 20

TABLE 4 Prefix Suffix Total Input TU Codeword code code codeword Valueprefix EG prefix suffix length length length 0 0 1 0 1 1 10 2 0 2 2 1103 0 3 3 111 0 4 0 4 4~5 111 10 x 5 1 6 6~9 111 110 xx 6 2 8 10~17 1111110 xxx 7 3 10 18~33 111 11110 xxxx 8 4 12 34~65 111 111110 xxxxx 9 514  66~129 111 1111110 xxxxxx 10 6 16 130~257 111 11111110 xxxxxxx 11 718 258~513 111 111111110 xxxxxxxx 12 8 20  514~1025 111 1111111110xxxxxxxxx 13 9 22 1026~2049 111 11111111110 xxxxxxxxxx 14 10 242050~4097 111 111111111110 xxxxxxxxxxx 15 11 26 4098~8193 1111111111111110 xxxxxxxxxxxx 16 12 28  8194~16385 111 11111111111110xxxxxxxxxxxxx 17 13 30 16386~32769 111 111111111111110 xxxxxxxxxxxxxx 1814 32

FIGS. 10 and 12 are flow diagrams of a method for encoding ALF filtercoefficients using a combination of coefficient position dependent shortcodes, i.e., exp-Golomb codes for some coefficient positions, where thevalue of k depends on the position, and fixed length codes (FLC) oforder S for other coefficient positions, where the value of S depends onthe position. FIGS. 11 and 13 are flow diagrams of the correspondingmethods for decoding ALF filter coefficients encoded using therespective methods of FIGS. 10 and 12. Tables 5 and 6 show the values ofk or S for each coefficient position. The range of the coefficientvalues in these tables differs from those of the other tables as thisparticular technique was tested in a version of ALF in which ALFcoefficient values were quantized before encoding. The particular valuesof k and S shown in FIGS. 10-13 and Tables 5 and 6, and the use of FLCor exp-Golomb for the particular coefficient positions are examples.Other suitable values of k and S may be used. For example, the values ofk and S may be determined as described above in reference to FIGS. 6 and7. Further, the particular code used for any given coefficient may bedifferent. As will be understood by one of ordinary skill in the art,the values of k, S, and the use of FLC or exp-Golomb may be differ forversions in which the ALF coefficient values are not quantized. Forthese examples, exp-Golomb was selected for coefficient positions havingvalues with a peaked distribution and FLC was selected for coefficientposition having values with a flat distribution.

TABLE 5 Filter Entropy coding Coefficient Syntax element coefficienttechnique value range alf_filt_coeff[0] C0 FLC5 −16 to 15alf_filt_coeff[1] C1 FLC6 −32 to 31 alf_filt_coeff[2] C2 FLC6 −32 to 31alf_filt_coeff[3] C3 FLC7 −64 to 63 alf_filt_coeff[4] C4 FLC6 −32 to 31alf_filt_coeff[5] C5 FLC4 −8 to 7 alf_filt_coeff[6] C6 FLC5 −16 to 15alf_filt_coeff[7] C7 FLC6 −32 to 31 alf_filt_coeff[8] C8 FLC7 −64 to 63alf_filt_coeff[9] C9 EG0 0 to 511

TABLE 6 Filter Entropy coding Coefficient Syntax element coefficienttechnique value range alf_filt_coeff[0] C0 EG0 −256 to 255alf_filt_coeff[1] C1 EG0 −256 to 255 alf_filt_coeff[2] C2 EG0 −256 to255 alf_filt_coeff[3] C3 FLC7 −64 to 63 alf_filt_coeff[4] C4 EG0 −256 to255 alf_filt_coeff[5] C5 EG0 −256 to 255 alf_filt_coeff[6] C6 EG0 −256to 255 alf_filt_coeff[7] C7 EG0 −256 to 255 alf_filt_coeff[8] C8 FLC7−64 to 63 alf_filt_coeff[9] C9 EG0 0 to 511

FIG. 14 is a flow diagram of a method for encoding ALF filtercoefficients using coefficient position independent short codes, e.g.,exp-Golomb codes of order k=0, . . . , 5, where the value of k is fixedfor all coefficient positions. FIG. 15 is a flow diagram of thecorresponding method for decoding ALF filter coefficients encoded usingthe method of FIG. 14. The particular value of k shown in FIGS. 14 and15 is an example. Other suitable values may be used. For example, thevalue of k may be determined empirically using a representative set ofvideo sequences, i.e., experiments may be conducted with differentvalues of k to find the value with the least distortion.

FIG. 16 is a flow diagram of a method for encoding ALF filtercoefficients in which no information is encoded for one of thecoefficient positions, thus reducing the number of bits needed to encodethe ALF coefficients. In this method, the symmetric filter isconstrained to be a unit gain filter such that the sum of thecoefficients is 1.0 (or some fixed point representation of 1.0, i.e.,C0+C1+C2+C3+C4+C5+C6+C7+C8+C9=1.0. Thus, given the values of nine of thecoefficients, the tenth one may be derived. In this example, thecoefficient value at position C9 is not encoded. Thus, given the valuesof C0, C1, C2, C3, C4, C5, C6, C7, C8, the value of C9 can be derived inthe decoder as C9=1.0−C0+C1+C2+C3+C4+C5+C6+C7+C8, thus eliminating theneed to encode a value for C9. FIG. 17 is a flow diagram of acorresponding method for decoding ALF filter coefficients encoded usingthe method of FIG. 16. One of ordinary skill in the art will understandembodiments of these methods for other filter shapes where the centercoefficient (or any other predetermined coefficient position) can becalculated from the remaining coefficients. In some embodiments, thesemethods may be used in conjunction with one of the above described shortcode encoding/decoding method pairs.

As currently proposed in HEVC, the values of the ALF coefficients forpositions 0-8 for chroma are coded without considering any bias presentin the chroma ALF coefficient values. Similarly, the values of the ALFcoefficients for luma are coded without considering any bias in thesecoefficient values. FIG. 18 illustrates the distributions of the chromaALF coefficients for a representative set of video sequences. As thisfigure shows, there is a bias in the chroma coefficient values,especially for coefficient positions 3 and 8, which have a bias around30, and coefficient positions 1 and 7, which have a bias around −10.FIG. 19 illustrates the distributions of the luma ALF coefficients for arepresentative set of video sequences. Removing or reducing the biasprior to entropy coding will increase coding efficiency.

FIG. 20 is a flow diagram of a method for encoding ALF filtercoefficients in which the bias is removed or reduced prior to entropycoding the values. This method may be used for both luma filtercoefficients and chroma filter coefficients. FIG. 21 is a flow diagramof a corresponding method for decoding ALF filter coefficients encodedusing the method of FIG. 20. Note that in the method of FIG. 20, a biasis subtracted from each coefficient value prior to encoding, and in themethod of FIG. 21, the bias is added back to each coefficient valueafter the bias-reduced value is decoded. In this embodiment, a uniquebias value is assumed for each coefficient position. Note that some ofthe bias values may be 0. In some embodiments, the bias values used bythe encoder and the decoder are defined by the coding standard. In someembodiments, the encoder signals the bias values to the encoder, e.g.,at the sequence level. In some embodiments, these methods may be used inconjunction with one of the above described short code encoding/decodingmethod pairs. In some embodiments, these methods may be used inconjunction with one of the above described short code encoding/decodingmethod pairs and the encoding/decoding method pair of FIGS. 16 and 17.

ALF coefficients values may be negative or positive. Further, thenegative values can have a different distribution than the positivevalues. For example, in FIG. 19, the positive values of coefficientposition 8 have a fat tailed distribution whereas the negative valueshave a thin tailed distribution. Thus, a unified entropy codingtechnique that codes negative and positive values with different orderentropy codes matched to the distribution may be used. For example,negative values can be coded with EG(0), and the positive values can becoded with EG(4) or vice versa. In another example, the negative valuescan be coded with a unary code, and positive values can be coded withEG(4) or vice versa.

FIG. 22 shows a flow diagram of a method for adaptive loop filtering ofa reconstructed picture in a video encoder. Initially, an encodedpicture is reconstructed 2200 in the embedded decoder of the videoencoder. Deblocking filtering is then applied 2202 to the reconstructedpicture. One or more sets of filter coefficients for the adaptive loopfilter are then determined 2204 for the picture. The determination ofthe set(s) of filter coefficients may be performed using any suitabletechnique. Adaptive loop filtering is then applied 2206 to thereconstructed picture according to the set(s) of filter coefficients.The sets of filter coefficients are then entropy encoded 2208 in the bitstream. The entropy encoding may be performed using an embodiment of oneof the methods of FIGS. 6, 8, 10, 12, 14, 16, and 20. Further, theentropy encoding may be performed using an embodiment of one of themethods of FIGS. 6, 8, 10, 12, and 14 and an embodiment of the method ofFIG. 16 and/or an embodiment of the method of FIG. 20.

FIG. 23 shows a flow diagram of a method for adaptive loop filtering ofa reconstructed picture in a video decoder. Initially, the set(s) offilter coefficients for a picture are entropy decoded 2300 from theencoded bit stream. The entropy decoding performs the inverse to theentropy encoding performed by the encoder that generated the bit stream.The entropy decoding may be performed using an embodiment of one of themethods of FIGS. 7, 9, 11, 13, 15, 17, and 21. Further, the entropydecoding may be performed using an embodiment of one of the methods ofFIGS. 7, 9, 11, 13, and 15, and an embodiment of the method of FIG. 17and/or an embodiment of the method of FIG. 21. The picture is alsodecoded 2302 from the encoded bit stream. Deblocking filtering isapplied 2304 to the reconstructed picture, followed by adaptive loopfiltering 2306 according to the set(s) of filter coefficients.

Embodiments of the methods, encoders, and decoders described herein maybe implemented for virtually any type of digital system (e.g., a desktop computer, a laptop computer, a tablet computing device, a netbookcomputer, a handheld device such as a mobile (i.e., cellular) phone, apersonal digital assistant, a digital camera, etc.). FIG. 24 is a blockdiagram of an example digital system suitable for use as an embeddedsystem that may be configured to entropy encode ALF coefficients asdescribed herein during encoding of a video stream and/or entropy decodeALF coefficients as described herein during decoding of an encoded videobit stream. This example system-on-a-chip (SoC) is representative of oneof a family of DaVinci™ Digital Media Processors, available from TexasInstruments, Inc. This SoC is described in more detail in “TMS320DM6467Digital Media System-on-Chip”, SPRS403G, December 2007 or later, whichis incorporated by reference herein.

The SoC 2400 is a programmable platform designed to meet the processingneeds of applications such as video encode/decode/transcode/transrate,video surveillance, video conferencing, set-top box, medical imaging,media server, gaming, digital signage, etc. The SoC 2400 providessupport for multiple operating systems, multiple user interfaces, andhigh processing performance through the flexibility of a fullyintegrated mixed processor solution. The device combines multipleprocessing cores with shared memory for programmable video and audioprocessing with a highly-integrated peripheral set on common integratedsubstrate.

The dual-core architecture of the SoC 2400 provides benefits of both DSPand Reduced Instruction Set Computer (RISC) technologies, incorporatinga DSP core and an ARM926EJ-S core. The ARM926EJ-S is a 32-bit RISCprocessor core that performs 32-bit or 16-bit instructions and processes32-bit, 16-bit, or 8-bit data. The DSP core is a TMS320C64x+TM core witha very-long-instruction-word (VLIW) architecture. In general, the ARM isresponsible for configuration and control of the SoC 2400, including theDSP Subsystem, the video data conversion engine (VDCE), and a majorityof the peripherals and external memories. The switched central resource(SCR) is an interconnect system that provides low-latency connectivitybetween master peripherals and slave peripherals. The SCR is thedecoding, routing, and arbitration logic that enables the connectionbetween multiple masters and slaves that are connected to it.

The SoC 2400 also includes application-specific hardware logic, on-chipmemory, and additional on-chip peripherals. The peripheral set includes:a configurable video port (Video Port I/F), an Ethernet MAC (EMAC) witha Management Data Input/Output (MDIO) module, a 4-bit transfer/4-bitreceive VLYNQ interface, an inter-integrated circuit (I2C) businterface, multichannel audio serial ports (McASP), general-purposetimers, a watchdog timer, a configurable host port interface (HPI);general-purpose input/output (GPIO) with programmable interrupt/eventgeneration modes, multiplexed with other peripherals, UART interfaceswith modem interface signals, pulse width modulators (PWM), an ATAinterface, a peripheral component interface (PCI), and external memoryinterfaces (EMIFA, DDR2). The video port I/F is a receiver andtransmitter of video data with two input channels and two outputchannels that may be configured for standard definition television(SDTV) video data, high definition television (HDTV) video data, and rawvideo data capture.

As shown in FIG. 24, the SoC 2400 includes two high-definitionvideo/imaging coprocessors (HDVICP) and a video data conversion engine(VDCE) to offload many video and image processing tasks from the DSPcore. The VDCE supports video frame resizing, anti-aliasing, chrominancesignal format conversion, edge padding, color blending, etc. The HDVICPcoprocessors are designed to perform computational operations requiredfor video encoding such as motion estimation, motion compensation,intra-prediction, transformation, quantization, and in-loop filtering.Further, the distinct circuitry in the HDVICP coprocessors that may beused for specific computation operations is designed to operate in apipeline fashion under the control of the ARM subsystem and/or the DSPsubsystem.

As was previously mentioned, the SoC 2400 may be configured to performentropy encoding of ALF coefficients as described herein during encodingof a video stream and/or entropy decoding of ALF coefficients asdescribed herein during decoding of an encoded video bit stream. Forexample, the coding control of the video encoder of FIG. 4 may beexecuted on the DSP subsystem or the ARM subsystem and at least some ofthe computational operations of the block processing, including theintra-prediction and inter-prediction of mode selection, transformation,quantization, and entropy encoding may be executed on the HDVICPcoprocessors. At least some of the computational operations of entropyencoding ALF coefficients during encoding of a video sequence may alsobe executed on the HDVICP coprocessors. Similarly, at least some of thecomputational operations of the various components of the video decoderof FIG. 5, including entropy decoding, inverse quantization, inversetransformation, intra-prediction, and motion compensation may beexecuted on the HDVICP coprocessors. Further, at least some of thecomputational operations of entropy decoding ALF coefficients duringdecoding of an encoded video bit stream may also be executed on theHDVICP coprocessors.

Other Embodiments

While the invention has been described with respect to a limited numberof embodiments, those skilled in the art, having benefit of thisdisclosure, will appreciate that other embodiments can be devised whichdo not depart from the scope of the invention as disclosed herein.

Embodiments of the methods, encoders, and decoders described herein maybe implemented in hardware, software, firmware, or any combinationthereof. If completely or partially implemented in software, thesoftware may be executed in one or more processors, such as amicroprocessor, application specific integrated circuit (ASIC), fieldprogrammable gate array (FPGA), or digital signal processor (DSP). Thesoftware instructions may be initially stored in a computer-readablemedium and loaded and executed in the processor. In some cases, thesoftware instructions may also be sold in a computer program product,which includes the computer-readable medium and packaging materials forthe computer-readable medium. In some cases, the software instructionsmay be distributed via removable computer readable media, via atransmission path from computer readable media on another digitalsystem, etc. Examples of computer-readable media include non-writablestorage media such as read-only memory devices, writable storage mediasuch as disks, flash memory, memory, or a combination thereof.

It is therefore contemplated that the appended claims will cover anysuch modifications of the embodiments as fall within the true scope ofthe invention.

What is claimed is:
 1. A method for adaptive loop filtering, the methodcomprising: determining a coefficient value of an adaptive loop filter;determining a bias of the coefficient value based on a coefficientposition of the coefficient value; altering the coefficient value toremove the bias; applying the adaptive loop filter to at least a portionof a reconstructed picture using the altered coefficient value; andentropy encoding the altered coefficient value into a compressed bitstream using a short binary code, wherein the short binary code useddepends on the coefficient position of the coefficient value.
 2. Themethod of claim 1, wherein the short binary code is an exp-Golomb code,wherein an order k of the exp-Golomb code for a first coefficientposition is different from an order k of the exp-Golomb code for asecond coefficient position.
 3. The method of claim 2, wherein the biasis determined based on a distribution of coefficient values at thecoefficient position of the coefficient value.
 4. The method of claim 2,wherein the adaptive loop filter is a unit gain filter and wherein asecond coefficient value of a second coefficient position is not entropyencoded in the compressed bit stream.
 5. The method of claim 1, furthercomprising signaling the bias for the coefficient in the compressed bitstream.
 6. The method of claim 1, wherein the short binary code for afirst coefficient position is different from the short binary code for asecond coefficient position.
 7. The method of claim 6, wherein the shortbinary code for the first coefficient is an exp-Golomb code and theshort binary code for the second coefficient position is a combinationof a truncated unary code and an exp-Golomb code.
 8. The method of claim6, wherein the short binary code for the first coefficient is anexp-Golomb code and the short binary code for the second coefficientposition is a fixed length code.
 9. A method for adaptive loopfiltering, the method comprising: entropy decoding a coefficient valuefrom a compressed video bit stream using a short binary code, whereinthe short binary code used depends on a coefficient position of thecoefficient value; and determining a bias of the coefficient value basedon a coefficient position of the coefficient value; altering thecoefficient value to add the bias; applying the adaptive loop filter toa portion of a reconstructed picture using the altered coefficientvalue.
 10. The method of claim 9, wherein the short binary code is anexp-Golomb code, wherein an order k of the exp-Golomb code for a firstcoefficient position is different from an order k of the exp-Golomb codefor a second coefficient position.
 11. The method of claim 10, whereinthe bias is determined based on a distribution of coefficient values atthe coefficient position of the coefficient value.
 12. The method ofclaim 10, wherein the adaptive loop filter is a unit gain filter andwherein a second coefficient value of a second coefficient position isnot entropy encoded in the compressed bit stream and wherein the secondcoefficient value is derived from the entropy decoded coefficientvalues.
 13. The method of claim 9, further comprising decoding the biasfor the coefficient value from the compressed video bit stream.
 14. Themethod of claim 9, wherein the short binary code for a first coefficientposition is different from the short binary code for a secondcoefficient position.
 15. The method of claim 14, wherein the shortbinary code for the first coefficient is an exp-Golomb code and theshort binary code for the second coefficient position is a combinationof a truncated unary code and an exp-Golomb code.
 16. The method ofclaim 14, wherein the short binary code for the first coefficient is anexp-Golomb code and the short binary code for the second coefficientposition is a fixed length code.